Preeclampsia is a severe disorder that affects 3-7% of all pregnancies. It is a leading cause of maternal and neonatal morbidity and mortality worldwide. Preeclampsia is characterized by new-onset hypertension and proteinuria after 20 weeks gestation. Left untreated, it can lead to maternal seizures, multi-organ failure, and death. Delivery is the only cure, which often necessitates preterm birth. Despite extensive investigation, the etiology of preeclampsia is poorly understood. Improved understanding of the disease could significantly improve clinical care for pregnant women. Recently metabolomics (i.e., metabolic profiling, meaning the examination of cellular metabolites such as sugars, amino acids, organic acids, nucleotides, and lipids) has emerged as a promising technique for understanding complex diseases, such as hypertension and type 2 diabetes. This approach is also useful for understanding disorders of pregnancy, since maternal metabolites represent the output of a network of interactions between maternal, fetal, and placental compartments. Initial metabolic profiling experiments in women with preeclampsia have demonstrated altered metabolites; however, these studies have significant limitations. Specifically, (1) the metabolic signatures reported in women with preeclampsia have been unique in each study; (2) subgroups of women with preeclampsia have been analyzed together (i.e., those with early- and late-onset disease); (3) only one time point in gestation has been analyzed in each study; (4) urine analysis is lacking from most studies. We propose here the first longitudinal, global metabolic profiling of both maternal plasma and urine in each trimester of pregnancy in women who developed early-onset preeclampsia (requiring delivery prior to 37 weeks). The samples for this analysis are already banked and ready for use. The cohort includes 2105 total women, 56 of whom developed early-onset preeclampsia. We will characterize the global metabolic profile in maternal blood and urine in women with early-onset preeclampsia and matched controls using well-established liquid chromatography tandem mass spectroscopy platforms. Changes in metabolites will be analyzed between trimesters for each patient. Additionally, differences in metabolites between preeclamptics and matched controls will be analyzed by trimester. We will then assess if the metabolic phenotype can identify subgroups of patients based on their clinical phenotypes with a focus on gestational age at delivery, infant birth weight, and abnormal laboratory studies. These experiments will define the metabolic profile throughout pregnancy in women who develop early-onset preeclampsia and will enhance our understanding of pathways involved in disease pathogenesis. Ultimately, this knowledge has the potential to lead to new predictive tests and treatments for preeclampsia.